Understanding spatial effects in species distribution models

Iosu Paradinas; Janine Illian; Sophie Smout

doi:10.1371/journal.pone.0285463

Peer Review History

Original SubmissionAugust 1, 2022
4 Oct 2022 Decision Letter - Judi Hewitt, Editor PONE-D-22-21589Understanding spatial effects in species distribution modelsPLOS ONE Dear Dr. Paradinas, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but has the potential to be improved by following the reviewer's suggestions in the attached file Please submit your revised manuscript by Nov 18 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. 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If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? 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Reviewer #1: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Paradinas et al., present a simulation study to assess how random spatial effects represent missing co-variates using two spatial models: a Generalised Additive Model (GAM) and a Bayesian spatial model (INLA). They demonstrate that fitted spatial effects resemble the sum of the unaccounted covariate surfaces in each model. The simulation approach is relatively simple (as acknowledged by the authors in the discussion) but clearly explained and relevant for the aims of the study. I have no major concerns with this study, however, I think the manuscript could benefit from some additional points in the introduction and discussion in order to further appeal to ecologists who may want to consider the results from this interesting study (see specific comments in attached file). ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. 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Revision 1
23 Nov 2022 Author Response Review: Understanding spatial effects in species distribution models Summary: Paradinas et al., present a simulation study to assess how random spatial effects represent missing co-variates using two spatial models: a Generalised Additive Model (GAM) and a Bayesian spatial model (INLA). They demonstrate that fitted spatial effects resemble the sum of the unaccounted covariate surfaces in each model. The simulation approach is relatively simple (as acknowledged by the authors in the discussion) but clearly explained and relevant for the aims of the study. I have no major concerns with this study, however, I think the manuscript could benefit from some additional points in the introduction and discussion in order to further appeal to ecologists who may want to consider the results from this interesting study (see specific comments below). Abstract & general comments to consider throughout the text I’m not sure I agree with “most SDMs include spatial effects”. Consider softening with “SDMs can account for random spatial effects which may improve prediction… etc”. Note that the use of random spatial effects is sometimes used in linear modelling (Bayesian or not) but less so for machine learning which are popular SDM algorithms (e.g., Random Forest, Boosted Regression Trees, Maxent, etc) – you could consider including this point somewhere in the MS – possibly in the discussion? We agree with the reviewer that it is better to soften the wording and we decided to use his recommendation. However, we may not comment anything on the no-use of spatial effects (as in geostatistics or 2D splines) in ML, maxent… methods as, in our opinion, does not provide any valuable point to the discussion topic. Note in my suggested wording above, I use the term “random spatial effects”. If the authors agree with this clarification. Suggest this term is used throughout the text, or at first mention to make clear. We decided not to use the term “random”. Even though Bayesian spatial effects are structured random effects, not all spatial effects are random. For instance, are 2D splines random effects? I’m assuming that throughout that the manuscript the authors are referring to SDMs fitted with occurrence data (the most common SDMs in my experience). If so, please make this very clear early on. If not, then further explanation is needed for how to interpret statements about Type I error for SDMs fitted with occurrence data AND with those fitted with abundance data (since for the latter, you may need to approach this as a hurdle model or delta model). The authors refer to “Type I errors”. I don’t disagree that this term is an accurate description, but I think many ecologists in the context of SDMs (where the null hypothesis is not clear) would have difficulty interpreting the statement. For example, if the authors are referring to SDM fitted with occurrence data, would type I refer to “false positive rate” and “false negative rate” i.e., misclassification of presences (predicted 0 when it should 1) and misclassification of absences (predicted 1 when it should 0)? Can you try and link this explanation to commonly used model fit metrics for SDMs such as TSS (True Skill Statistic) which specifically deal with sensitivity and specificity? This is an interesting comment. In fact, this is an abundance SDM using a Poisson. By Type I error, we mean “mistaken rejection of an actually true null hypothesis”, or in SDM terms, identifying a environmental driver as significant while in reality isn’t. This should be the same whether the response variable is occurrence, abundance, or biomass, thus should be the same in a hurdle model. Again, I’m not sure I agree with the statement “Ecologists tend to try ecologically interpret the spatial patterns displayed by the spatial effect” suggest softening it to “In some cases ecologists try to ecologically interpret the spatial patterns displayed by the spatial effect” since some SDM studies are principally concerned with predictive ability rather than interpretation of drivers. We agree that softening our original terms is good. We have now changed these as suggested. Suggest instead of “This study wants to provide a practical demonstration” the authors use “This study aims to provide a practical demonstration” We thank the reviewer. It reads better now :) Suggest that the authors generalise the description of the methods to “Generalised Additive Model” and shortened to “GAM” and “Bayesian spatial model” when generally referring to the methods in the intro / discussion – in my experience this terminology is more informative / commonly used than “2D smoothing splines” and “geostatistic model” respectively. Here, as with the random spatial effect suggestion, we may prefer to keep it as it is. Indeed, the term GAM is widely used to refer to models that include splines, but reality is that a gaussian linear model is also a GAM. Similarly, spatial model may refer to different things, as there are different spatial models (lattice, point, etc.). In fact, geostatistics do not necessarily have to be applied in the Bayesian framework. Therefore, we prefer to be specific about the methodology and use geostatistics and 2D splines. Introduction: L 8-10: I think the authors need to broaden this out to link this more with ecology. Suggest rejigging this sentence to reflect the below points 1. ideally co-variates (spatial and non-spatial) would fully explain the relationship between species occurrence or abundance with biotic and abiotic factors (you could briefly explain this in the context of ecological niches?). 2. In practice this isn’t possible since it’s really complicated (you mention this in the discussion) and the co-variates we have aren’t always accurate. 3. Random spatial or spatial/temporal effects can be incorporated in SDMs to proxy for unaccounted for processes which have a spatial, temporal, spatial-temporal structure (i.e., missing co-variates / unaccounted for interactions between co-variates). We thank the reviewer for this comment as we believe that it has helped improve the MS. The edited text is in the first paragraph of the MS and highlighted in blue L8 – 9: Can you also provide examples of each co-variate in brackets? E.g., assuming that “non-spatial covariates” would be things like year, month? Yes, indeed, this was a good suggestion, but we have decided to remove this sentence after expanding the text based on the previous suggestion. We believe that the text reads a lot better now, and the distinction between spatial and non-spatial covariates is not that important for the purpose of this MS. L14 -16: my above point about proxying for unaccounted for co-variates is relevant here. I agree with the authors but suggest that you clarify that these are due to “unaccounted environmental or biotic drivers” which are often variables which are hard to measure or estimate, e.g., “geographical range dispersion process, e.g. colonisation and other highly dynamic processes such as wind and current”. We have now re-written this paragraph. The edited part is highlighted in blue. L17 – 23: very good points about scale L43: suggest remove “novel” L46: suggest remove “rather” L47: I’m not familiar with the terminology “model-based spatial models” Can you not simply call these “spatial models”? Or simplify some other way? We have edited our text according to all the above suggestions. Model-based spatial model essentially refers to spatial models that include covariates as opposed to those spatial models that are purely spatial. Simulation: Suggest that you need to clarify somewhere in this section: • whether your SDMs are occurrence • that you calculated the residuals (table 2) and what these represent (i.e., deviations predicted from actual empirical values of data – which comes back to the units need to be clarified) Our SDMs are Poisson models. This section begins mentioning “at each iteration we added a fixed number of new specimens…” which implies abundance, but we have now added Poisson spatial models in line 61. Regarding the mention about residuals, we made a mistake naming the column that way in tables 2, 3 and 4. Instead, we have now named it “dispersion” as it refers to the spatial aggregation derived from the simulated dispersion process of the species. L50: depending on the formatting requirements of the journal, this may be better called “methods” We agree with the reviewer and the section is now called “methods”. L52: this is a good example of an often-omitted co-variate which random spatial effects are often interpreted as representing. Suggest you (briefly) revisit this in the discussion. Indeed. We have now mentioned this in the first sentence of the discussion section. L64-66: see suggestions on model terminology. Also need to state whether you used default settings (which I assume you did). Yes indeed, this is now included in the MS Results: L93 – 95: suggest this is discussion rather than results. Indeed, we have now moved this into the discussion Discussion: L99: suggest need a reference as an example for this statement It´s been hard to find a reference for this statement. However, it is a rather well L104 -105: suggest, “Here, we did not attempt to account for all possible cases, instead, we aimed to illustrate our point using a simple and intuitive approach.” We thank the reviewer for this suggestion. The entire sentence has been edited as suggested. L124 – 126: Agree that this can increase predictive capacity, but only within sampled areas (i.e., interpolation between sample points). Although extrapolation isn’t encouraged, in many cases SDMs are spatially predicted into areas with low samples where random spatial effects provide no additional benefit (especially if they override the effects of other co-variates which are important drivers). I think you could mention this caveat. That is, to use spatial effects with care when the aim if prediction. This is an interesting point, but we have decided not to discuss much about this in the MS. We did a bunch of trials but we finally concluded that they deviated the discussion, and therefore we have simply edited the text so that it is clear that spatial effects improve prediction within the sampled area. Attachments Attachment Submitted filename: Response_to_reviewers.docx https://doi.org/10.1371/journal.pone.0285463.r002
1 Dec 2022 Decision Letter - Judi Hewitt, Editor PONE-D-22-21589R1Understanding spatial effects in species distribution modelsPLOS ONE Dear Dr. Paradinas, Thank you for submitting your manuscript to PLOS ONE. While you have largely met the reviewer's suggestions, in re-reading the manuscript I did pick up one further point. IN the introduction you mention " one can accommodate the spatial or spatio-temporal structure of the data that is unaccounted by our covariates". Post that the focus is on spatial effects. Could you either remove the spatio-temporal comment or actually include how temporal changes to spatial structures (or real species- environment relationships) may alter your results. Please submit your revised manuscript by Jan 15 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Judi Hewitt Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0285463.r003
Revision 2
18 Apr 2023 Author Response This version contains the last edit requested by the editor. We have removed the mention of spatiotemporal effects as we finally decided that it would only confuse the reader. Attachments Attachment Submitted filename: Response_to_reviewers.docx https://doi.org/10.1371/journal.pone.0285463.r004
25 Apr 2023 Decision Letter - Judi Hewitt, Editor Understanding spatial effects in species distribution models PONE-D-22-21589R2 Dear Dr. Paradinas, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Judi Hewitt Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0285463.r005
Formally Accepted
19 May 2023 Acceptance Letter - Judi Hewitt, Editor PONE-D-22-21589R2 Understanding spatial effects in species distribution models Dear Dr. Paradinas: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Judi Hewitt Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0285463.r006

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